# time series

1. ### How do I turn the n-ahead ARIMA predictions to undifferenced values?

Hello everyone, I`m doing a Monthly sales forecast based on some historical data. My question is when I do the Arima(p,d,q) and then I do forecast(arima_model) in order to get the fitted values, which are nicely following the historical data points, then If I take the mean values from the...
2. ### Why do we differentiate between log linear vs. exponential time series

Given by definition for a function to be linear on a log plot, it must be exponential (bc log_a(e^x)=x), why do we differentiate between log linear and exponential things?
3. ### Spurious Regression with non stationary time-series

Hi everyone, I'd like to have a confirmation on the correctness of the following interpretation: Let say that we want to run a very simple regression like the following one: We are regressing two I(1) series since x and y are assumed to be both described by a random walk process. The errors of...
4. ### "Decreasing P-value" could be interpreted as "Getting Meaningful?" in time series?

Hello. I'm Lee, a candidate for a master's degree in business administration in South Korea. I'm analyzing economic data in emerging markets such as Asia, And I found that many indicators are following incumbent markets such as U.S. or E.U. And the basis for that is the p-value in simple...
5. ### How to test the variability of count data over time

I'm wondering how I might best test for over-dispersion of raw count data over time. I have just started a project and am exploring my data, so I do not have a model to test on. I have 4000 independent customers and the frequency of their purchases per day for 44 days. I must determine whether...
6. ### Uncovered interest rate parity

Hi all I have to proof that the uncovered interest rate parity is hold if c_2(s)=E_1[c_2]. The two first order conditions are given as: Then I simpliefied this: I think, if the Cov-Term equals zero, the UIP is fullfilled. Could it be that the Cov-Term is zero, since our...
7. ### De-trending before regression analysis

I'm currently analysing two sets of time series data (monthly temperature and forest cover over a 10 year period). I first ran a Mann Kendall on each variable (they're non-normal) after removing seasonality, and found that they both show a significant increasing trend - vegetation faster than...
8. ### Dealing with definition changes mid time series

Can anyone point me in the direction of how I can deal with an abrupt change midway through a time series. The change is suspected to be due to data collection changes, not genuine and it is a significant shift in level but not trend. by 'deal with' I mean I need to be able to assess how things...
9. ### Test temporal change in standard deviation

Very dear geeks :cool:! I am new in this forum. I am a french post-doc in marine ecology and I am especially interested in trophic relationships. I am currently analyzing time series. I have to admit that time series are definitely one of my strongest Achilles heels, I am actually afraid of...
10. ### Is it allowed to reduce a dataset of moving averages to run an AR(1) model properly?

I run a simple AR(1) and AR(2) model with the following R-code: ar.ols(df$y, order.max = 1) ar.ols(df$y, order.max =2) My dataset is as follows: I do have yearly data and calculate generational averages, whereas one generation is equal to 30 years. In order to allow for overlapping...
11. ### Interpreting the result of a Bayesian Structural Times Series model

A bit of context: I am reading a study called "Exploring the determinants of Bitcoin Price". In this research paper google search trends across different countries over time are used, in part, to determine price movements in Bitcoin. They use a Bayesian Structural Times Series model. I am...
12. ### How can be used time series in sport?

Hello, noob here in statistics. How can be time series be useful to sport stats modelling? Let's take as an examplem footbal
13. ### plot mean value according to confidence interval

Hi all, i have a very simple question, because i am not good at statistics but i need that :) I have two signals, one is lets say 'x' another is 'time', so its a time serie. I need to find the upper and lower values of my signals according to confidence interval and then show them on a graph...
14. ### Time Series modeling --criteria

Give criteria for aiding in the choice of a “best” time series model when two or more such models are available. What is, arguably, the most important criterion? I think that for the above, isn't the AIC, BIC the most arguable? I would look at autocorrelation plots, but I am trying to see what...
15. ### Comparing quantitative parameter between two groups with only one of these having repeated measures

My question regards the best way of comparing two groups for differences in the levels of several quantitative parameters. Here, for only one of the groups there are 4 repeated measurements at different intervals. The data -We have two groups we want to compare: one consists of ~200 patients at...
16. ### Interpretation of log transformed first differences in SVAR models

I am working with a structural VAR analysis, and want to understand my results. The model studies how a shock on one variable affects a second variable. I understand that if the first month's response is +3 %, it means that the initial value of the response variable increases by 3 percent...
17. ### Using a dummy variable to model threshold effects

Hi All, I'm new to this thread and very green/inexperienced in using regressions. I'm trying to model threshold effects in a time series analysis - for instance, does an output hike of 5% or greater lead to a different effect on returns than when the output change is less than 5%. Given that I...
18. ### Calculate fits of Markov Switching AR (1) model

I have created a MS-AR(1) model in EViews 9.5 (the software I'm working with) and I'm just trying to understand how some of the output is calculated. This is really dumb and probably a simple question to answer, but I can't seem to get how the fitted values are calculated. I have tried...
19. ### updating ARIMA model

When should one use the different types of ARIMA model as mentioned below: Estimate the model order in the training data set and use the same order to forecast future values (updating the parameter estimates) Use a rolling window (e.g. 30 day )to make a new forecast by estimating model order...
20. ### When to use Augmented Dickey Fuller test vs Dickey Fuller Test - Time series

Checking a variable for I(1) process, when should i use a ADF vs DF test?